An individual's genetic makeup influences their susceptibility to disease or disorder, and can also affect disease severity, prognosis, and even treatment options. Most genetic variants exert subtle effects in isolation, and are thus maintained in the population. However, certain combinations of variants are incompatible; yet it remains poorly understood how an accumulation of small genetic perturbations can compromise normal homeostasis and sensitize a tissue to disorder. The current project will characterize how natural genetic variation segregating in a sensitized population interacts to disrupt the buffering capacity of a transcription network during organ development. The proposed research will take a systems genetics approach to model the transcription network in the embryonic mouse gonad during sex determination. The gonad arises at mid-gestation competent to differentiate as a testis or ovary irrespective of sex chromosome constitution. This unique plasticity is conferred by a balanced transcriptome with features associated with both differentiated sexual fates. Failure to establish or maintain one sexual fate (e.g. testis) causes sex reversal to the alternative fate (e.g. ovary). Genetic background is known to affect susceptibility to sex reversal by unbalancing the underlying transcription network. The proposed sensitized screen will introduce a background-dependent sex-reversing mutation to sensitize a genetic mapping population to sex reversal. This highly diverse population of genetically unique individuals, the Diversity Outbred (DO) stock, is derived from the same eight founder strains as the emerging Collaborative Cross (CC) recombinant inbred strains, and captures genome-wide high levels of genetic variation and provides high mapping resolution. Aim 1 will characterize the expression of a subset of known sex determination genes in gonads from the DO panel, eight CC founder strains, and the sex-reversing Dax1/Nr0b1 mutant strain. This survey will provide a baseline measurement of expression variability in the DO population and enable the modeling of an undirected transcription network based on coexpression relationships. Aim 2 will derive a large population of DO embryos that are sensitized to sex reversal by the Dax1/Nr0b1 mutation. Regions of the genome that affect gene expression in the gonad (expression quantitative trait loci, or eQTL) will be identified from a combination of RNA-Seq expression and dense genotyping data. The resulting eQTL data will be used to develop a detailed predictive network model of sex determination.